Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	16,090
2	New Jersey	13,928
3	Massachusetts	9,613
4	Rhode Island	8,768
5	Connecticut	8,214
6	District of Columbia	6,797
7	Louisiana	6,268
8	Delaware	5,173
9	Illinois	4,616
10	Michigan	4,324
11	Maryland	4,048
12	Pennsylvania	3,989
13	South Dakota	2,925
14	Indiana	2,866
15	Colorado	2,798
16	Nebraska	2,756
17	Iowa	2,738
18	Georgia	2,568
19	Mississippi	2,500
20	Virginia	2,077
21	Washington	2,003
22	Tennessee	1,822
23	New Hampshire	1,786
24	New Mexico	1,779
25	Nevada	1,749
26	Kansas	1,660
27	Ohio	1,654
28	Florida	1,650
29	Utah	1,553
30	Alabama	1,552
31	North Dakota	1,513
32	Vermont	1,419
33	California	1,360
34	Missouri	1,328
35	Wisconsin	1,315
36	South Carolina	1,260
37	Arizona	1,149
38	Arkansas	1,117
39	Minnesota	1,104
40	North Carolina	1,097
41	Kentucky	1,092
42	Texas	1,083
43	Idaho	1,067
44	Oklahoma	973
45	Maine	857
46	Wyoming	741
47	West Virginia	660
48	Oregon	624
49	Puerto Rico	549
50	Alaska	496
51	Hawaii	431
52	Montana	425

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Rhode Island	327
2	District of Columbia	326
3	Massachusetts	290
4	New Jersey	279
5	Nebraska	251
6	Connecticut	235
7	New York	227
8	Illinois	214
9	Maryland	199
10	Iowa	189
11	Delaware	131
12	Pennsylvania	127
13	Kansas	118
14	Virginia	108
15	Louisiana	106
16	Indiana	105
17	Tennessee	104
18	Mississippi	97
19	Michigan	94
20	Georgia	93
21	Minnesota	93
22	New Hampshire	91
23	Colorado	83
24	New Mexico	82
25	South Dakota	80
26	Wisconsin	65
27	Ohio	57
28	Arizona	53
29	North Dakota	52
30	Utah	50
31	Nevada	49
32	North Carolina	49
33	Alabama	46
34	Texas	41
35	California	40
36	Missouri	39
37	South Carolina	39
38	Washington	38
39	Florida	35
40	Puerto Rico	33
41	Oklahoma	31
42	Kentucky	25
43	Maine	23
44	Arkansas	18
45	Idaho	14
46	Oregon	14
47	Wyoming	14
48	West Virginia	13
49	Vermont	12
50	Alaska	4
51	Hawaii	1
52	Montana	1

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	972
2	New Jersey	871
3	Connecticut	683
4	Massachusetts	557
5	Louisiana	419
6	Michigan	402
7	District of Columbia	340
8	Rhode Island	279
9	Pennsylvania	218
10	Illinois	203
11	Maryland	191
12	Delaware	172
13	Indiana	165
14	Colorado	144
15	Georgia	109
16	Washington	109
17	Mississippi	97
18	Ohio	87
19	Nevada	83
20	Vermont	81
21	Virginia	72
22	Minnesota	70
23	New Mexico	66
24	Florida	63
25	New Hampshire	61
26	Missouri	60
27	Oklahoma	60
28	Alabama	58
29	Wisconsin	57
30	California	56
31	Kentucky	56
32	Iowa	55
33	South Carolina	51
34	Arizona	48
35	Kansas	48
36	Maine	41
37	North Carolina	40
38	Nebraska	39
39	Idaho	35
40	Tennessee	32
41	North Dakota	31
42	Texas	30
43	West Virginia	27
44	Oregon	25
45	Arkansas	23
46	South Dakota	23
47	Puerto Rico	16
48	Utah	15
49	Montana	14
50	Wyoming	12
51	Hawaii	11
52	Alaska	9

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	New Jersey	36
2	Connecticut	25
3	Massachusetts	21
4	District of Columbia	16
5	New York	15
6	Rhode Island	14
7	Michigan	11
8	Louisiana	10
9	Pennsylvania	10
10	Illinois	9
11	Maryland	9
12	Delaware	8
13	Indiana	7
14	Minnesota	4
15	Mississippi	4
16	New Hampshire	4
17	New Mexico	4
18	Colorado	3
19	South Dakota	3
20	Virginia	3
21	Arizona	2
22	California	2
23	Florida	2
24	Georgia	2
25	Iowa	2
26	Missouri	2
27	Nevada	2
28	North Dakota	2
29	Ohio	2
30	Oklahoma	2
31	South Carolina	2
32	Vermont	2
33	Alabama	1
34	Arkansas	1
35	Kentucky	1
36	Nebraska	1
37	North Carolina	1
38	Texas	1
39	Washington	1
40	West Virginia	1
41	Wisconsin	1
42	Alaska	0
43	Hawaii	0
44	Idaho	0
45	Kansas	0
46	Maine	0
47	Montana	0
48	Oregon	0
49	Puerto Rico	0
50	Tennessee	0
51	Utah	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	119,107	1	99
Lincoln	Arkansas	62,730	2	99
Dakota	Nebraska	47,039	3	99
Nobles	Minnesota	41,565	4	99
Bledsoe	Tennessee	39,565	5	99
Davidson	Tennessee	4,142	222	92
Richland	South Carolina	2,275	490	84
Pierce	Washington	1,646	705	77
Orange	California	838	1228	60
York	South Carolina	779	1308	58

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Randolph	Georgia	2,803	1	99
Terrell	Georgia	2,227	2	99
Early	Georgia	1,963	3	99
Nassau	New York	1,597	4	99
Essex	New Jersey	1,583	5	99
Richland	South Carolina	91	526	83
Pierce	Washington	57	733	76
Davidson	Tennessee	40	908	71
Orange	California	16	1278	59
York	South Carolina	11	1360	56

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.